Maneuver Marketing - Data Analyst
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Requirements
• Experience with automation, AI-powered analytics, performance marketing, and eCommerce environments is highly desirable. • Advanced SQL — window functions, CTEs, complex joins, query optimisation • Proficient in at least one BI tool — Tableau, Power BI, Looker, Metabase, or similar • Experience with a cloud data warehouse — BigQuery, Snowflake, Redshift, or Databricks • Experience with data transformation tools and ETL concepts — dbt, Databricks, or equivalent • Strong Excel or Google Sheets for ad-hoc analysis • Experience using AI tools for automation, workflow improvement, or analytics • Structured problem-solving — breaks ambiguous business questions into clear analytical frameworks • Independently identifies trends, risks, and opportunities without a specific brief • Awareness of analytical models — subscription LTV, cohort analysis, funnel metrics • Familiarity with A/B testing methodology — experiment design and hypothesis testing • Communication, Collaboration & Adaptability • Communicates findings clearly to both technical and non-technical audiences • Adapts output and framing for different stakeholders — executives, growth, product, operations • Collaborative across functions; coordinates effectively with VAs and cross-functional teams • Comfortable with ambiguity, shifting priorities, and self-directed learning • 3 to 5 years in Data Analytics, Business Intelligence, or a related field • Proven experience independently building dashboards, automated reporting and strategic analysis • The following are strong-to-have — candidates without all of these are still encouraged to apply. • Experience in eCommerce, DTC, subscription, or consumer goods • Proficiency in Python or R for data manipulation or workflow automation • Familiarity with marketing KPIs — CAC, ROAS, MER, LTV:CAC, contribution margin • Familiarity with marketing concepts: customer journey mapping, funnel analysis, cohort retention, incrementality testing • Experience with A/B testing or experimentation frameworks • Experience with ETL processes, API data extraction, or data pipeline tooling • Familiarity with additional databases — PostgreSQL, MySQL, MongoDB, or Azure SQL • Experience implementing AI-powered analytics workflows or reporting automation • Success in the First 12 Months • Own and automate reporting across key business functions, reducing manual effort and improving data • Independently build and maintain data pipelines in collaboration with engineering and operations, • reducing dependency on manual data pulls • Drive analytical ownership for the Growth team — from campaign performance to retention and product • Deliver insights that directly influence marketing efficiency, budget allocation, and promotional • Improve visibility into product and promotional performance across SKUs and channels • Coordinate VAs effectively on data tasks, ensuring quality and consistency of outputs • Develop sufficient working knowledge of DTC marketing and subscription concepts to provide • commercially grounded analysis • Enable leadership to make faster, better-informed decisions through accessible, trustworthy data
Responsibilities
• Reporting & Dashboard Ownership • Own and maintain the company-wide reporting infrastructure, including dashboards, KPI trackers, and automated reports • Build, improve, and manage recurring reports for Growth, Marketing, Product, Finance, and Operations teams • Design and develop executive-level dashboards that support leadership decision-making • Manage and iterate on existing dashboards, updating metrics, adding dimensions, and evolving reporting as the business changes • Own data quality and governance, metric definitions, documentation, and reporting standards • Ensure accuracy, consistency, and reliability of all business metrics and data outputs • Data Pipeline & Automation • Partner with engineering and operational teams to improve data collection, tracking, and pipeline reliability • Leverage AI tools and advanced analytics techniques to improve reporting efficiency and insight generation • Independently build and maintain data pipelines using dbt or equivalent to support clean, reliable analytical layers • Growth & Marketing Analytics • Partner closely with the Growth team to analyze performance across paid media channels • Evaluate campaign performance, customer acquisition trends, CAC, ROAS, MER, LTV, retention, and other growth metrics • Conduct deep-dive analyses to identify growth opportunities and performance drivers • Analyze promotional performance and measure the impact of marketing initiatives • Product & Commercial Analysis • Monitor and evaluate product performance across SKUs, channels, and markets • Analyze purchasing patterns, customer segmentation, pricing impact, and promotional effectiveness • Identify opportunities to improve product assortment, pricing decisions, and inventory allocation • Provide recommendations based on quantitative analysis and business impact • Ad-Hoc Analysis & Decision Support • Respond to analytical requests from cross-functional teams with structured, business-ready outputs • Investigate business challenges, identify root causes, and present actionable recommendations • Support experimentation and A/B testing efforts — helping design tests, interpreting results, and communicating outcomes to stakeholders • Translate complex datasets and quantitative findings into clear narratives for non-technical • Analytical Operations • Coordinate and manage VAs on data-related tasks — scoping work, reviewing outputs, maintaining quality • Flag data integrity issues proactively and drive resolution across relevant teams • Support experimentation and hypothesis testing as the role and business matures
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